Welcome to our group website

We are working in quantum technologies with a focus in implementations of quantum computation and quantum simulation with quantum optical systems. Our research could be applied towards developing exotic high-performance quantum processors and simulators, and also for fundamental science in the area of strongly correlated quantum systems. read more.

July 2026: Our theoretical proposal from two years ago has now been experimentally realised by collaborators at USTC, using an ultracold-atom processor with 20 atoms across 64 sites, and published in Physical Review X. The quantum experiment completed a sampling task in ~500 seconds — a task that would take the Frontier supercomputer at least eight days — demonstrating a ~1000x quantum advantage. Congratulations to everyone involved, including former group member Supanut and all team members who contributed along the way! You can read more about the work here, in this CQT highlight article.
June 2026: Group member Muhammad has recently submitted another work onto the arXiv which shows that circuit design choices can cut measurement overhead in variational quantum algorithms by 25–55%. Tested on the nonlinear Schrödinger equation ground state problem, the results demonstrate a practical path toward more resource-efficient quantum algorithms on NISQ devices!
March 2026: Check out our latest work now on the arXiv by group members Spyros and Muhammad. We present a new low-depth method for executing CNOT ladder circuits by trading circuit depth for width using mid-circuit measurements and classical control, reducing errors from limited qubit coherence. Congratulations to the team on the great work!
March 2026: Our recent work by group members Harvey and Daniel has now been published! Here we introduce a nonlinear Schrödinger model linking wave dynamics to topological invariants from persistent homology, revealing robust soliton and flat-top beam formations for controlling nonlinear waves in optics and Bose–Einstein condensates.
November 2025: We recently submitted a paper onto arXiv where we demonstrate a new approach to qubit-efficient optimization by framing it as a geometrical problem, aligning the quantum representation with the inherent structure of the problem itself. This work establishes a direct link between a mathematical concept called the Sherali-Adams polytope and the consistency required for accurate quantum computation, resulting in a streamlined process that requires significantly fewer qubits. This method achieves impressive results on challenging optimization tasks, surpassing existing approaches and paving the way for more powerful and efficient quantum algorithms by leveraging the underlying geometry of the problem – congrats to Gordon!
July 2025: Check out our latest work now on the arXiv by group members Eleftherios, Muhammad, and collaborators (arXiv link will be available from 29/7/25). This paper presents a resource-efficient, low-depth Hadamard test circuit and tailored variational ansatz for NISQ devices, significantly reducing gate counts. The approach accurately simulates nonlinear Burgers’ dynamics and remains resilient to hardware noise, showing strong agreement with classical benchmarks. Please reach out if you have any questions or are interested to find out more!
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Research Highlights

June 2022: Topological data analysis and machine learning

Topological data analysis and machine learning Daniel Leykam, Dimitris G. Angelakis arXiv:2206.15075 Topological data analysis refers to approaches for systematically …

July 2021: Fock State-enhanced Expressivity of Quantum Machine Learning Models

Fock State-enhanced Expressivity of Quantum Machine Learning Models Beng Yee Gan, Daniel Leykam, Dimitris G. Angelakis EPJ Quantum Technology 9 …

Jan 2021: Photonic band structure design using persistent homology

Photonic band structure design using persistent homology D. Leykam, D. G. Angelakis APL Photonics 6, 030802 (2021)  The machine learning …

December 2020: Quantum supremacy and quantum phase transitions

Quantum supremacy and quantum phase transitions S. Thanasilp, J. Tangpanitanon, M. A. Lemonde, N. Dangniam, D. G. Angelakis Phys. Rev …

July 2020: Qubit efficient algorithms for binary optimization problems

Qubit efficient algorithms for binary optimization problems B. Tan, M. A. Lemonde, S. Thanasilp, J. Tangpanitanon, D. G. Angelakis Quantum …

May 2020: Expressibility and trainability of parameterized analog quantum systems for machine learning applications

Expressibility and trainability of parameterized analog quantum systems for machine learning applications J. Tangpanitanon, S. Thanasilp, M. A. Lemonde, N …